The use of honey in healing a recalcitrant wound following surgical treatment of hidradenitis suppurativa

Ancient civilizations used honey to heal wounds. Despite the rediscovery of honey by modern physicians1 its use in conventional medicine, unlike in complementary medicine, remains limited. Much anecdotal evidence, some clinical observations, some animal models and some randomised controlled trials support the efficacy of honey in managing wounds2,3 , but few detailed descriptions of the use of honey in healing difficult surgical wounds have previously been published

Model for Quantitative Estimation of Functionality Influence on the Final Value of a Software Product

The gap between software development requirements and available resources of software developers continues to widen. This requires changes in the development and organization of software development. This study introduced a quantitative software development management methodology that estimates the relative importance and risk of functionality retention or abundance, which determines the final value of the software product. The final value of a software product is interpreted as a function of its requirements and functionalities, represented as a computational graph (called a software product graph). The software product graph allows the relative importance of functionalities to be estimated by calculating the corresponding partial derivatives of the value function. The risk of not implementing functionality was estimated by reducing the product's final value. This model was applied to two EU projects, CareHD and vINCI. In vINCI, functionalities with the most significant added value to the application are developed based on the implemented model, and those related to the least value are abandoned. Optimization was not implemented in the CareHD project, and proceeded as initially designed. Consequently, only 71% of the CareHD potential value was achieved. The proposed model enables rational management and organization of software product development with real-time quantitative evaluation of functionalities impacts and, assessment of the risks of omitting them without a significant impact. Quantitative evaluation of the impacts and risks of retention or abundance is possible based on the proposed algorithm, which is the core of the model. This model is a tool for the rational organization and development of software products

Anomaly Detection and Anticipation in High Performance Computing Systems

In their quest toward Exascale, High Performance Computing (HPC) systems are rapidly becoming larger and more complex, together with the issues concerning their maintenance. Luckily, many current HPC systems are endowed with data monitoring infrastructures that characterize the system state, and whose data can be used to train Deep Learning (DL) anomaly detection models, a very popular research area. However, the lack of labels describing the state of the system is a wide-spread issue, as annotating data is a costly task, generally falling on human system administrators and thus does not scale toward exascale. In this article we investigate the possibility to extract labels from a service monitoring tool (Nagios) currently used by HPC system administrators to flag the nodes which undergo maintenance operations. This allows to automatically annotate data collected by a fine-grained monitoring infrastructure; this labelled data is then used to train and validate a DL model for anomaly detection. We conduct the experimental evaluation on a tier-0 production supercomputer hosted at CINECA, Bologna, Italy. The results reveal that the DL model can accurately detect the real failures, and, moreover, it can predict the insurgency of anomalies, by systematically anticipating the actual labels (i.e., the moment when system administrators realize when an anomalous event happened); the average advance time computed on historical traces is around 45 minutes. The proposed technology can be easily scaled toward exascale systems to easy their maintenance

An Explainable Model for Fault Detection in HPC Systems

Large supercomputers are composed of numerous components that risk to break down or behave in unwanted manners. Identifying broken components is a daunting task for system administrators. Hence an automated tool would be a boon for the systems resiliency. The wealth of data available in a supercomputer can be used for this task. In this work we propose an approach to take advantage of holistic data centre monitoring, system administrator node status labeling and an explainable model for fault detection in supercomputing nodes. The proposed model aims at classifying the different states of the computing nodes thanks to the labeled data describing the supercomputer behaviour, data which is typically collected by system administrators but not integrated in holistic monitoring infrastructure for data center automation. In comparison the other method, the one proposed here is robust and provide explainable predictions. The model has been trained and validated on data gathered from a tier-0 supercomputer in production

Why honey is effective as a medicine. 1. Its use in modern medicine

Honey has been used as a medicine for thousands of years and its curative properties are well documented. However, modern medicine turned its back on honey and it is only now, with the advent of multi-resistant bacteria, that the antibiotic properties of honey are being rediscovered

The Antibacterial Activity of Honey Derived from Australian Flora

Chronic wound infections and antibiotic resistance are driving interest in antimicrobial treatments that have generally been considered complementary, including antimicrobially active honey. Australia has unique native flora and produces honey with a wide range of different physicochemical properties. In this study we surveyed 477 honey samples, derived from native and exotic plants from various regions of Australia, for their antibacterial activity using an established screening protocol. A level of activity considered potentially therapeutically useful was found in 274 (57%) of the honey samples, with exceptional activity seen in samples derived from marri (Corymbia calophylla), jarrah (Eucalyptus marginata) and jellybush (Leptospermum polygalifolium). In most cases the antibacterial activity was attributable to hydrogen peroxide produced by the bee-derived enzyme glucose oxidase. Non-hydrogen peroxide activity was detected in 80 (16.8%) samples, and was most consistently seen in honey produced from Leptospermum spp. Testing over time found the hydrogen peroxide-dependent activity in honey decreased, in some cases by 100%, and this activity was more stable at 4°C than at 25°C. In contrast, the non-hydrogen peroxide activity of Leptospermum honey samples increased, and this was greatest in samples stored at 25°C. The stability of non-peroxide activity from other honeys was more variable, suggesting this activity may have a different cause. We conclude that many Australian honeys have clinical potential, and that further studies into the composition and stability of their active constituents are warranted

Tiller Population Density and Sward Stability of Brachiaria brizantha Continuously Stocked by Cattle

Tiller population density is one the most important parameters of sward structure and its evaluation is normally included in studies of sward dynamics. Moreover, a greater level of understanding is achieved when the survival of successive tiller generations is monitored. (Matthew et al., 2000). This would help to explain seasonal variation in tiller populations based on tiller appearance and death rates. While Brachiaria brizantha c.v. Marandu occupies up to 70 million hectares of cultivated grassland in Brazil, little is known of its ecophysiology. The objective of this work was to calculate survival probability of B. brizantha tillers and identify seasonal variation on sward stability

Herbage Intake and Animal Performance of Cattle Grazing \u3cem\u3eBrachiaria brizantha\u3c/em\u3e cv. Marandu Under Continuous Stocking

Grazing management affects sward structure, which in turn influences plant and animal responses. With the objective of understanding causal relationship between sward structure and animal responses, the present experiment evaluated the daily herbage intake and live weight gain of growing cattle on Brachiaria brizantha cv. Marandu pasture during summer (Dec. 2001 to Mar. 2002)

Prevalence of toxoplasmic retinochoroiditis in an Australian adult population: A community-based study

Purpose: Toxoplasmic retinochoroiditis is the most common clinical manifestation of an infection with the protozoan parasite, Toxoplasma gondii. Up to 50 % of the human population is estimated to be infected with T. gondii; however, the epidemiology of toxoplasmic retinochoroiditis has not been widely reported. We sought to estimate the prevalence of toxoplasmic retinochoroiditis in Australia using data that were collected as part of the Busselton Healthy Ageing Study. Design: oss-sectional, community-based, prospective cohort study. Participants: 5020 Australian adults (2264 men and 2756 women; age range, 45–69 years, and median age, 58 years). Methods : Retinal color photographs, centered on the optic disc and macula, were captured using a digital retinal camera after the dilation of the pupils. Three uveitis-subspecialized ophthalmologists assessed each pigmented retinal lesion, and complete concordance of opinion was required to assign a toxoplasmic etiology. Serum T. gondii immunoglobulin (Ig)G levels were measured for those participants with retinal lesions judged to be toxoplasmic retinochoroiditis. Main Outcome Measures : Prevalence of toxoplasmic retinochoroiditis. Results: Eight participants (0.16 %) had retinal lesions that were considered to have the characteristic appearance of toxoplasmic retinochoroiditis, plus detectable serum T. gondii IgG, consistent with the diagnosis of toxoplasmic retinochoroiditis. On the assumption that 23.81 % of retinal lesions occur at the posterior pole, as reported in a community-based survey conducted in Brazil (Sci Rep. 2021;11:3420), the prevalence of toxoplasmic retinochoroiditis was estimated to be 0.67 % or 1 per 149 persons. Conclusions: Toxoplasmic retinochoroiditis is common in Australian adults. Efforts to quantify and address risk factors for human infection with T. gondii are justified